Algorithms will save the day

As we continue our journey to transform the online business at Staples, one thing we’re using to guide our product and technology roadmap is automation. We need to optimize on several axes – speed of operations, (and actual throughput), efficiency, correctness, and cost.

Given the size of the business at Staples (the various online pieces combined are several billion dollars a year), we’re moving as much heuristics as possible into automated decision making systems. This will allow us to improve end-to-end throughput, while optimizing revenue and profit, and reducing cost. Similarly, all incidents will be tagged and tracked, so we can do root cause analysis, eliminate potential sources of defects, and even stop the line if needed.

Take, for example, our new expanded catalog. For a long time (over 25 years), we sold less than 30,000 SKUs, all related to office supplies. In the past year or so, we’ve rapidly expanded our assortment. We’re adding whole slews of products, one vertical at a time. For instance, we recently added hospitality, and retail. If you’re a business in those industries, you can now not only buy your office supplies from us, but anything else you need to run your business. You run a restaurant? Buy your cleaning supplies, cutlery, glassware, etc. from us as well.

We recently crossed 500,000 SKUs on offer, and are on track to cross 2 million soon, and over 5 million within a couple of years. The question, of course, is how to market these new products and to whom. Manually devising strategies to market to the right target audiences has its place, of course. At the Innovation Lab, we set our data scientists to work on this problem. By analyzing all available data on the millions of customers we already have, we’re able to figure out what industries a large number of them belong to. We can then automatically show them relevant new products when they log on, or when we send out promotional emails.

Even where we don’t have comprehensive information about our customers, we can computationally determine several things about them. For instance, can you guess the industry someone within an email address of belongs to?

Another example is shipment delivery estimates. We already have a world class logistics platform, having been in the business of receiving orders, fulfilling them, and getting them out to our customers within one business day. As we expand our SKUs though, a larger and larger number of our products will be dropshipped by our vendor partners. The variability on these items is much higher, and the shipments tend to be slightly slower as well. By using historical data around inventory levels, handling times, and shipping carriers’ actual delivery tracking data, we’re able to predict when an item is going to reach a shopper with a very high degree of precision. By communicating this to our customers up front, we’re able to provide a much better experience online.

These are just examples of the several projects we have in the works here at the San Mateo based Staples Innovation Lab. Others include things like real-time selling price optimization, smarter personalized email content targeting, dynamic and personalized product bundles, hyper-personalized product recommendations, a new e-commerce search engine, and several others, for this year alone.

The path forward is clear – automation is the key, and algorithms will save the day 🙂

P. S. – Watch for these project as they go live on And if you’re a technologist, interested in joining the journey we’re on, email me at, or check out

It’s always Day 2 at Staples

It’s been over two months since Runa was acquired and we became Staples Innovation Lab. I’ve been meaning to write about this transition, but things have just been so busy. I do think it’s important that I record this journey though, because in a few years time, people will look around and will wonder at the steep rise of Staples. 🙂

We started Runa with the same gleam in our eyes as most Silicon Valley startups – of changing the face of the industry we were in. We chose e-commerce, even though in 2008, it wasn’t exactly sexy. Those were the years of the consumer startups, and no one was even looking at enterprise focused deals. My own viewpoint though was, and still is, that the e-commerce story is still being written. I’m an shareholder, I’ve been using their service ever since I moved to this country over 10 years ago, and I’m a huge fanboy. My appreciation for Jeff Bezos is paralleled only by my admiration for Steve Jobs. has literally defined e-commerce… and is overwhelming every other contender in the space. 

So we started Runa with one overarching goal. To help e-commerce merchants survive the onslaught. The idea was that most retailers aren’t technology companies, and don’t have the capabilities to battle Amazon, one of the most advanced tech companies in the world. Further, these folks are unlikely to ever grow such capabilities in-house, for a whole variety of reasons. At Runa, we built out a set of SaaS products, each focused on a specific area. All these services were built on top of a big-data + machine-learning stack. Our output was a run-time platform that ran predictive models to address individual aspects of the shopping experience. Merchants simply plugged our APIs into their world, and we enabled their site.

For instance, we built PerfectOffer to help merchants stop giving away discounts, indiscriminately, to everyone. Our platform built sophisticated statistical models of the behavior of the shoppers, and then in real-time would determine which shopper should get what deal on what product. Or even if they should get an offer at all. Not only was the discount spend made far more efficient (which helped average gross margins), but it also had a highly non-linear positive impact on net margins. Another service we built was called PerfectShipping, which used past seller performance and shipment tracking data to figure out when shoppers could expect to receive their items, with a high degree of confidence, even if merchants used the cheapest carrier services. Online marketplaces and retailers alike used this to take on Amazon Prime’s 2-day free shipping, and the incremental sales numbers this service generated for our large merchants was incredible. Other services included PerfectEmail and PerfectBundles.

By the time Runa was acquired, we were able to count some very large retailers as our customers, including eBay, Groupon, and Target. In July this year, we added Staples. Now, to be clear, we had never thought Staples was a particularly relevant company… actually, I had never really given much thought to Staples at all. However, once they became a customer, I did find out a fair bit about them, and things seemed quite impressive. It turns out, Staples is the world’s second largest e-commerce player, after Sure, it’s a distant second, but it does make over 10 billion dollars a year online. Remember, this is despite them not being a tech company. Not in any realistic sense of the word.

So when they talked to us about a strategic partnership, and they described where they wanted to go, I realized that this could be an incredible opportunity. My vision for Runa was always this set of AI programs that would drive all aspects of an e-commerce operation. We would use data to optimize just about everything, and all in real-time, all automated. This would drive down costs, and would then allow for lower margins, which would mean cheaper prices for shoppers. And all the while, it would have the amazing side-effect of improving the customer experience. Staples, in my mind, was the perfect place to put this into action. Kind of like a PerfectPlayground 🙂

Staples is an old company – they’re 27 years old, and they’re still a brick-n-mortar retailer at heart. This is changing, and there’s a lot to be done. The reality though is that it was a startup at one point, and that entrepreneurial spirit is still alive. The first phase of the company, in a sense, was the retailer phase, and they opened thousands of stores around the world. All are (or certainly were) amazing cash-generating machines, and even today, even as the the face of stores business is changing, they’ll continue to generate the cash needed to help the overall company as a whole.

I like to think of the offline business as Day 1 for Staples, and we’re now on Day 2. This is going to be a long day, since we’re never going to be done. The good news is that there’s tremendous upside as we execute on this path to becoming a technology company ourselves. There’s much work to be done, and much software to be written. There are plenty of business processes to change. There are plenty of people to win over, Wall Street analysts included. The glory is in the challenge, of course, and this is one heck of a challenge. How does one attempt to build what a company like has built over the past 15 years (at least the relevant e-commerce bits) in a span of just 2-3 years? This is a tech challenge, a people challenge, a process challenge, and a business challenge. It means we can’t do things in the typical, traditional manner. We’ve made very different technology choices (Lisp, anyone?) and are asking all the crazy people we can find, the doers, to join us. The enemy is formidable, but one thing’s for sure: it’s going to be one hell of a fight.

It’s always Day 2 at Staples.